Privacy-enhancing distributed protocol for data aggregation based on blockchain and homomorphic encryption

Regueiro, Cristina; Seco, Iñaki; Diego, Santiago de; Lage, Oscar; Etxebarria, Leire

doi:10.1016/j.ipm.2021.102745

Cited by 29 publications

(12 citation statements)

References 25 publications

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“…The reason is that the proposed clustering method effectively uses the network's total energy and ulti- That is why nodes consume less energy and have less computational cost as given in [5], [52]. Ropsten environment is used for PoW while Rinkeby is used for PoA [53].…”

Section: Simulation Resultsmentioning

confidence: 99%

A Blockchain-Based Deep-Learning-Driven Architecture for Quality Routing in Wireless Sensor Networks

Khan

Amjad

Ahmed³

et al. 2023

IEEE Access

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Over the past few years, great importance has been given to wireless sensor networks (WSNs) as they play a significant role in facilitating the world with daily life services like healthcare, military, social products, etc. However, heterogeneous nature of WSNs makes them prone to various attacks, which results in low throughput, and high network delay and high energy consumption. In the WSNs, routing is performed using different routing protocols like low-energy adaptive clustering hierarchy (LEACH), heterogeneous gateway-based energy-aware multi-hop routing (HMGEAR), etc. In such protocols, some nodes in the network may perform malicious activities. Therefore, four deep learning (DL) techniques and a real-time message content validation (RMCV) scheme based on blockchain are used in the proposed network for the detection of malicious nodes (MNs). Moreover, to analyse the routing data in the WSN, DL models are trained on a state-of-the-art dataset generated from LEACH, known as WSN-DS 2016. The WSN contains three types of nodes: sensor nodes, cluster heads (CHs) and the base station (BS). The CHs after aggregating the data received from the sensor nodes, send it towards the BS. Furthermore, to overcome the single point of failure issue, a decentralized blockchain is deployed on CHs and BS. Additionally, MNs are removed from the network using RMCV and DL techniques. Moreover, legitimate nodes (LNs) are registered in the blockchain network using proof-of-authority consensus protocol. The protocol outperforms proof-ofwork in terms of computational cost. Later, routing is performed between the LNs using different routing protocols and the results are compared with original LEACH and HMGEAR protocols. The results show that the accuracy of GRU is 97%, LSTM is 96%, CNN is 92% and ANN is 90%. Throughput, delay and the death of the first node are computed for LEACH, LEACH with DL, LEACH with RMCV, HMGEAR, HMGEAR with DL and HMGEAR with RMCV. Moreover, Oyente is used to perform the formal security analysis of the designed smart contract. The analysis shows that blockchain network is resilient against vulnerabilities.

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Section: Simulation Resultsmentioning

confidence: 99%

A Blockchain-Based Deep-Learning-Driven Architecture for Quality Routing in Wireless Sensor Networks

Khan

Amjad

Ahmed³

et al. 2023

IEEE Access

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“…Cecchetti et al proposed a system that supports strict confidentiality and high transaction rates for bank intermediary accounts, using a variant of ELGamal-based Confidential Transactions (CT) to hide transaction amounts [18]. [24]. Overall, applying blockchain technology to data sharing in cloud environments has a considerable theoretical basis and research results.…”

Section: Privacy Protection In Blockchainmentioning

confidence: 99%

“…Egueiro et al. proposed an enhanced privacy‐preserving distributed secure data aggregation protocol based on blockchain and homomorphic encryption technologies which is used for data encryption, allowing private aggregation operations, and smart contracts facilitate efficient data aggregation [24].…”

Section: Related Workmentioning

confidence: 99%

FGDB‐MLPP: A fine‐grained data‐sharing scheme with blockchain based on multi‐level privacy protection

Lin,

Feng,

Wang

et al. 2024

IET Communications

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In the era of 5G, billions of terminal devices achieve global interconnection and intercommunication, which leads to the generation of massive data. However, the existing cloud‐based data‐sharing mechanism faces challenges such as sensitive information leakage and data islands, which makes it difficult to achieve secure sharing across domains. In this paper, the authors propose a fine‐grained data‐sharing scheme based on blockchain and ciphertext policy attribute‐based encryption, and design a verifiable outsourced computation method to reduce the computational pressure of end users. Second, the authors comprehensively consider the user's identity privacy and transaction privacy, and propose a multi‐level privacy protection method based on ring signature and garbled bloom filter, which enhance the user's data privacy and availability, and prevent the traceability of requests. Finally, the authors design a set of interconnected smart contracts, and verify that their scheme can achieve secure and efficient data sharing through security analysis and performance testing.

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“…Another method for sharing and manipulating data without revealing private values is homomorphic encryption [16].A typical example is RSA encryption. Under the modulo operation, the encrypted ciphertext multiplication result can be the same as the plaintext calculation.…”

Section: Homomorphic Encryptionmentioning

confidence: 99%

Comparison of current blockchain privacy protection technologies and prospects for future trends

Zheng¹

2023

Second International Conference on Green Communication, Network, and Internet of Things (CNIoT 2022)

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A decentralized, unchanging, and verifiable public ledger that can track the exchange of digital assets is provided by the blockchain. After Bitcoin brought out the blockchain, the blockchain is used in new fields such as smart cities and e-health, and plays a very important role. Although the decentralization of the blockchain makes the construction of digital currency possible, its open and transparent design also risks leaking user privacy. In order to fulfill the security needs of blockchain applications for privacy related information, the relevant researchers have recently done research on blockchain privacy protection challenges and posted corresponding protection technologies, a few of which have been also successfully implemented in several prevailing blockchain applications. In view of the blockchain privacy protection technology issues, this paper investigates the latest progress of blockchain privacy protection technology, conducts a comparative analysis, and summarizes at the end, so as to make an outlook on future trends.

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Privacy-enhancing distributed protocol for data aggregation based on blockchain and homomorphic encryption

Cited by 29 publications

References 25 publications

A Blockchain-Based Deep-Learning-Driven Architecture for Quality Routing in Wireless Sensor Networks

A Blockchain-Based Deep-Learning-Driven Architecture for Quality Routing in Wireless Sensor Networks

FGDB‐MLPP: A fine‐grained data‐sharing scheme with blockchain based on multi‐level privacy protection

Comparison of current blockchain privacy protection technologies and prospects for future trends

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